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DEPR: DataFrame.median/mean with numeric_only=None and dt64 columns #49250
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Original file line number | Diff line number | Diff line change |
---|---|---|
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@@ -73,14 +73,13 @@ def assert_stat_op_calc( | |
f = getattr(frame, opname) | ||
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if check_dates: | ||
expected_warning = FutureWarning if opname in ["mean", "median"] else None | ||
df = DataFrame({"b": date_range("1/1/2001", periods=2)}) | ||
with tm.assert_produces_warning(expected_warning): | ||
with tm.assert_produces_warning(None): | ||
result = getattr(df, opname)() | ||
assert isinstance(result, Series) | ||
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||
df["a"] = range(len(df)) | ||
with tm.assert_produces_warning(expected_warning): | ||
with tm.assert_produces_warning(None): | ||
result = getattr(df, opname)() | ||
assert isinstance(result, Series) | ||
assert len(result) | ||
|
@@ -390,21 +389,20 @@ def test_nunique(self): | |
def test_mean_mixed_datetime_numeric(self, tz): | ||
# https://github.com/pandas-dev/pandas/issues/24752 | ||
df = DataFrame({"A": [1, 1], "B": [Timestamp("2000", tz=tz)] * 2}) | ||
with tm.assert_produces_warning(FutureWarning): | ||
result = df.mean() | ||
expected = Series([1.0], index=["A"]) | ||
result = df.mean() | ||
expected = Series([1.0, Timestamp("2000", tz=tz)], index=["A", "B"]) | ||
tm.assert_series_equal(result, expected) | ||
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@pytest.mark.parametrize("tz", [None, "UTC"]) | ||
def test_mean_excludes_datetimes(self, tz): | ||
# https://github.com/pandas-dev/pandas/issues/24752 | ||
# Our long-term desired behavior is unclear, but the behavior in | ||
# 0.24.0rc1 was buggy. | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Remove this comment? |
||
# As of 2.0 with numeric_only=None we do *not* drop datetime columns | ||
df = DataFrame({"A": [Timestamp("2000", tz=tz)] * 2}) | ||
with tm.assert_produces_warning(FutureWarning): | ||
result = df.mean() | ||
result = df.mean() | ||
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expected = Series(dtype=np.float64) | ||
expected = Series([Timestamp("2000", tz=tz)], index=["A"]) | ||
tm.assert_series_equal(result, expected) | ||
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def test_mean_mixed_string_decimal(self): | ||
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@@ -857,6 +855,7 @@ def test_mean_corner(self, float_frame, float_string_frame): | |
def test_mean_datetimelike(self): | ||
# GH#24757 check that datetimelike are excluded by default, handled | ||
# correctly with numeric_only=True | ||
# As of 2.0, datetimelike are *not* excluded with numeric_only=None | ||
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df = DataFrame( | ||
{ | ||
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@@ -870,10 +869,9 @@ def test_mean_datetimelike(self): | |
expected = Series({"A": 1.0}) | ||
tm.assert_series_equal(result, expected) | ||
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with tm.assert_produces_warning(FutureWarning): | ||
# in the future datetime columns will be included | ||
with tm.assert_produces_warning(FutureWarning, match="Select only valid"): | ||
result = df.mean() | ||
expected = Series({"A": 1.0, "C": df.loc[1, "C"]}) | ||
expected = Series({"A": 1.0, "B": df.loc[1, "B"], "C": df.loc[1, "C"]}) | ||
tm.assert_series_equal(result, expected) | ||
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def test_mean_datetimelike_numeric_only_false(self): | ||
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I'm thinking we should rename this test (starting L397 here) as we're no longer testing that mean excludes datetimes.